Summary

THEORY: Crime is a social phenomenon
which evokes fear as a consequence, and this fear of crime affects people not
only at their place of residence or work, but also while travelling. Traditional methods for measuring fear of
crime employ static household survey questionnaires. This limits the type of
information that can be gathered on the times and spaces when people feel
fearful. What’s more, the surveys do not
capture actual experiences, but rely on recall, which is known for being
affected by issues with memory.

PURPOSE: The purpose of this data
collection technique is to collect data that will provide insight into when and
where fear of crime is experienced, and by whom. This allows for a holistic understanding of
perceptions of security covering people’s entire activity space (i.e. all
places people interact with day-to-day). Collecting data on people’s perceptions and experiences as they occur in
space and time allows us to identify, at the micro-level, what areas are
perceived as safe and unsafe, and know precisely how that changes with
different demographic groups, times of the day, days of the week, or other
variables. This knowledge can be used to design targeted, efficient and
effective situational interventions to enhance perceptions of safety in the
built environment.

METHOD: The Fear of Crime Application (FOCA)
is deployed as a questionnaire on a mobile device. It is a powerful way of seeking information
from people during (and about) their daily activities. Utilising in-built
sensors of phones allows for real-time collection of spatial (GPS) and temporal
(time and date) information about the report. This means that when a
participant answers the question “In this moment how worried are you about
becoming a victim of crime?” information is collected about their
characteristics, when and where they feel worried, as well as their answer.

Participants download the application from an app store onto their own
mobile devices before filling out a quick demographic survey. Participants are subsequently
sent reminders or “ping”s to complete the questionnaire. This can be set to
remind them at certain times (e.g. during morning peak travel times and evening
peak travel times) or in certain locations (e.g. when they come within 50
meters of Camden Town Station). Participants can either complete the survey
questionnaire about their fear of crime levels when the ping is sent, or at a
non-ping time (if they want to record an experience outside of this time). Retrospective annotation option is also
offered for participants if they would prefer to remove themselves from a
dangerous situation before using their (potentially) valuable phones. The data
collected contains demographic information (who sent the report), GPS (where it
was sent from), date and time (when it was sent), what the person felt (fear of
crime), which option they used to send the report (responding to a ping,
voluntarily, or retrospectively), and any additional questions put to
participants (in this case whether they are on public transport or not).

APPLICATION: To determine the feasibility of this
method, a pilot study was conducted. We recruited a convenience sample of 27
people. Participants submitted a total of 467 data points over the course of
two weeks. Number of reports per person varied from a minimum of 2 (one a week)
and a maximum of 44 (over 3 a day). On average, people submitted 16 reports
(over 1 each day) which, it can be argued, give a good insight into how people
experience fear of crime in the day-to-day.

Purpose and theory

THEORY: Crime is a social phenomenon which evokes fear as a consequence, and this
fear of crime affects people not only at their place of residence or work, but
also while travelling. Higher fear of
crime is associated with less cycling and walking, increased use of private
transport, and can act as a barrier to travel. To encourage use of public
transport, perception of safety during the entire door-to-door journey needs to
be better understood in order to be improved.

Traditional methods for measuring fear of crime apply household survey
questionnaires, where respondents are typically asked whether they are ‘very’,
‘fairly’, ‘not very’ or ‘not at all’ worried about becoming a victim of crime.
Such research omits many of the complexities involved with experiencing fear of
crime in everyday life. Instead, these measures often reflect generalised
attitudes towards risk and future-oriented anxieties, rather than actual
experiences. Recall-based surveys that ask participants about their experiences
in the past 3 -12 months are also affected by issues with recollection. Memories of emotional experience from longer
than about two-weeks draw on general knowledge from people’s beliefs rather
than the specifics of the event itself.

Data collected by retrospective questionnaires is further
restricted in terms of level of detail provided about when and where fear of
crime is experienced. Geographically it is usually restricted to views of the
residents of an area, and excludes perceptions of people who travel to or
through that area (e.g. people who work there, or who walk through that
neighbourhood to catch the train). Temporally (i.e. by time) we normally get a
“during the day” and “after night” division, which leaves no way of telling if
there are peak times for fear of crime within all hours of darkness. Inaccurate
measurement – in space or time - can lead to misguided interventions and wasted
public agency resources. Even experts struggle to consistently identify areas
of high crime (e.g. mapping crime hotspots helped show that police perceptions
of crime patterns do not always correlate with where the most crimes are
recorded). The same may be true for fear
of crime. In order to gain insight into
the nature of fear of crime, a new method of measurement is needed that
captures these dynamics.

PURPOSE: The purpose of this technique is to collect data that will provide insight
into when and where fear of crime is experienced, and by whom. This allows for a holistic understanding of
perceptions of security covering people’s entire activity space (i.e. all
places people interact with day-to-day). Data collected by this method is not
restricted by traditional limitations. Instead, collecting data on people’s
perceptions and experiences as they occur in space and time allows us to
identify, at the micro-level, what areas are perceived as safe and unsafe, and
know precisely how that changes with different demographic groups, times of the
day, days of the week, or other variables. This knowledge can be used to design
targeted, efficient and effective situational interventions to enhance
perceptions of safety in the built environment.

Method

The Fear of Crime Application (FOCA) is a data collection
technique that samples people’s everyday experiences to provide space, time,
and individual information about fear of crime in their entire activity space
(all places people interact with day-to-day).

The FOCA is deployed as a questionnaire on a mobile device. It is a powerful way of seeking information
from people during (and about) their daily activities. Utilising in-built
sensors of phones allows for real-time collection of spatial (GPS) and temporal
(time and date) information about the report. This means that when a
participant answers the question “In this moment how worried are you about
becoming a victim of crime?” information is collected about their
characteristics, when and where they feel worried, as well as their answer. The
following will outline and illustrate how this works:

1. Participants download the application from an app store onto
their own mobile devices.

2. The first time the app is launched, users fill out a quick
demographic survey to collect information such as age, gender, etc. This only
needs to be completed once, and is linked to all submitted reports.

3. Participants are sent reminders or “ping”s to complete the
questionnaire. This can be set to remind them at certain times (e.g. during
morning peak travel times and evening peak travel times) or in certain
locations (e.g. when they come within 50 meters of Camden Town Station).

4. When participants receive this ping they open the application
and complete the survey questionnaire about their current state.

5. Participants can also report something un-prompted. So if
they experience a fear of crime event at a non-ping time, they can still send a
report about it.

6. Retrospective annotation option is also offered for
participants if they would prefer to remove themselves from a dangerous
situation before using their (potentially) valuable phones. In this version
participants are offered the option of finding the location of the event on the
map, and telling how many hours ago the incident happened, allowing for an
adjusted GPS and time-stamp value that is still accurate to the report.

7. Finally the data collected will contain demographic
information (who sent the report), GPS (where it was sent from), date and time
(when it was sent), what the person felt (fear of crime), which option they
used to send the report (responding to a ping, voluntarily, or retrospectively),
and any additional questions put to participants (in this case whether they are
on public transport or not) (Figure 1).

Case Study

APPLICATION: The Fear of Crime Application (FOCA) is
a data collection technique that samples people’s everyday experiences to
provide space, time, and individual information about fear of crime in their
entire activity space (all places people interact with day-to-day).

To determine the feasibility
of this method, a pilot study was conducted. We recruited a convenience sample
of 27 people. In traditional experience sampling studies (studies that seek
information about everyday activities and experiences), sample sizes of 5 to 10
are common, and so in comparison 27 participants is a good number for this type
of study. Participants submitted a total of 467 data points over the course of
two weeks. Number of reports per person varied from a minimum of 2 (one a week)
and a maximum of 44 (over 3 a day). On average, people submitted 16 reports
(over 1 each day) which, it can be argued, give a good insight into how people
experience fear of crime in the day-to-day.

The majority of the reports
were “Not at all worried” reports (86.5%), followed by “Not very worried”
(9.4%), “Fairly worried” (3.6%), and “Very worried” (only 2 reports). Data
about time and location of reports revealed multiple reviews of the same
locations, which will allow for the creation of collective ‘fear maps’ (see for
example Figure 3 for the pilot map), and a good distribution of reports
throughout different hours of the day (Figure 2).

Another finding from the pilot was that there was a
miss-match between the pre-experiment questionnaire and the reports – meaning
three people did not complete it before they began the study. This was assumed
to be because they had to do this as a separate online form. To make it easier to fill in, and as a
pre-requisite, this has now been changed to all be done within the app.

Overall, the preliminary
results from the pilot study demonstrate that this methodology can be used to
collect dynamic spatial, temporal, and individual data about fear of crime
experienced in everyday life in a holistic manner that covers people’s entire
activity space.

Figure 2 - Reports received for each hour of the day

This method is not
restricted by problems of recall, or tied to static representations of time and
place. The map also illustrates the variation in fear of crime in very small
areas, which highlights the need for precise spatial data. To ensure that
limited policing or public agency resources are targeted effectively to problem
areas and times, this method can be utilised to collect the data that can then
inform such policy and planning decisions.